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3. Time series and mel frequency analyses of wet and dry cough signals : a neural net classificationAmmini Renjini, Mohanachandran Nair Sindhu Swapna, K. Satheesh Kumar, Sankaranarayana Iyer Sankararaman, 2023, original scientific article Keywords: time series, mel frequency, cough signal, wet cough, dry cough, phase portrait, mel coefficients, fractal dimension, neural network
Published in RUNG: 29.09.2023; Views: 727; Downloads: 5
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6. Downscaling of sample entropy of nanofluids by carbon allotropes : a thermal lens studyMohanachandran Nair Sindhu Swapna, Vimal Raj, S. Sreejyothi, K. Satheesh Kumar, Sankaranarayana Iyer Sankararaman, 2020, original scientific article Abstract: The work reported in this paper is the first attempt to delineate the molecular or particle dynamics from the thermal lens signal of carbon allotropic nanofluids (CANs), employing time series and fractal analyses. The nanofluids of multi-walled carbon nanotubes and graphene are prepared in base fluid, coconut oil, at low volume fraction and are subjected to thermal lens study. We have studied the thermal diffusivity and refractive index variations of the medium by analyzing the thermal lens (TL) signal. By segmenting the TL signal, the complex dynamics
involved during its evolution is investigated through the phase portrait, fractal dimension, Hurst exponent, and sample entropy using time series and fractal analyses. The study also explains how the increase of the photothermal energy turns a system into stochastic and anti-persistent. The sample entropy (S) and refractive index analyses of the TL signal by segmenting into five regions reveal the evolution of S with the increase of enthalpy. The lowering of S in CAN along with its thermal diffusivity (50%–57% below) as a result of heat-trapping suggests
the technique of downscaling sample entropy of the base fluid using carbon allotropes and thereby opening a novel method of improving the efficiency of thermal systems.
Keywords: carbon allotropic nanofluids, time series, entropy, MWCNT, thermal lens signal
Published in RUNG: 30.06.2022; Views: 1221; Downloads: 0
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7. Soot effected sample entropy minimization in nanofluid for thermal system design : a thermal lens studyMohanachandran Nair Sindhu Swapna, Vimal Raj, K. Satheesh Kumar, Sankaranarayana Iyer Sankararaman, 2020, original scientific article Abstract: The present work suggests a method of improving the thermal system efficiency, through entropy minimisation,
and unveils the mechanism involved by analysing the molecular/particle dynamics in soot nanofluids (SNFs)
using the time series, power spectrum, and wavelet analyses of the thermal lens signal (TLS). The photothermal
energy deposition in the SNF lowers the refractive index due to the temperature rise. It triggers the particle dynamics that are investigated by segmenting the TLS and analysing the refractive index, phase portrait, fractal dimension (D), Hurst exponent (H), and sample entropy (SampEn). The wavelet analysis gives information about
the relation between the entropy and the frequency components. When the phase portrait analysis reflects the
complex dynamics from region 1 to 2 for all the samples, the SampEn analysis supports it. The decreasing
value of D (from 1.59 of the base fluid to 1.55 and 1.52) and the SampEn (from 1.11 of the base fluid to 0.385
and 0.699) with the incorporation of diesel and camphor soot, indicate its ability to lower the complexity, randomness, and entropy. The increase of SampEn with photothermal energy deposition suggests its relation to
the thermodynamic entropy (S). The lowering of thermal diffusivity value of the base fluid from
1.4 × 10−7 m2/s to 1.1 × 10−7 and 0.5 × 10−7 m2
/s upon diesel and camphor soot incorporation suggests the
heat-trapping and reduced molecular dynamics in heat dissipation.
Keywords: soot, entropy, thermal system, photothermal, time series, nanofluid, fractal
Published in RUNG: 30.06.2022; Views: 1146; Downloads: 0
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